ECMWF extreme forecast index for water vapor transport: a forecast tool for atmospheric rivers and extreme precipitation

[thumbnail of Open Access]
Preview
Text (Open Access) - Published Version
· Available under License Creative Commons Attribution Non-commercial No Derivatives.
· Please see our End User Agreement before downloading.
| Preview

Please see our End User Agreement.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Lavers, D. A. orcid id iconORCID: https://orcid.org/0000-0002-7947-3737, Pappenberger, F. orcid id iconORCID: https://orcid.org/0000-0003-1766-2898, Richardson, D. S. and Zsoter, E. (2016) ECMWF extreme forecast index for water vapor transport: a forecast tool for atmospheric rivers and extreme precipitation. Geophysical Research Letters, 43 (22). pp. 11852-11858. ISSN 0094-8276 doi: 10.1002/2016GL071320

Abstract/Summary

In winter, heavy precipitation and floods along the west coasts of midlatitude continents are largely caused by intense water vapor transport (integrated vapor transport (IVT)) within the atmospheric river of extratropical cyclones. This study builds on previous findings that showed that forecasts of IVT have higher predictability than precipitation, by applying and evaluating the European Centre for Medium-Range Weather Forecasts Extreme Forecast Index (EFI) for IVT in ensemble forecasts during three winters across Europe. We show that the IVT EFI is more able (than the precipitation EFI) to capture extreme precipitation in forecast week 2 during forecasts initialized in a positive North Atlantic Oscillation (NAO) phase; conversely, the precipitation EFI is better during the negative NAO phase and at shorter leads. An IVT EFI example for storm Desmond in December 2015 highlights its potential to identify upcoming hydrometeorological extremes, which may prove useful to the user and forecasting communities.

Altmetric Badge

Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/106884
Identification Number/DOI 10.1002/2016GL071320
Refereed Yes
Divisions No Reading authors. Back catalogue items
Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher American Geophysical Union
Download/View statistics View download statistics for this item

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Search Google Scholar